Nonlinear Actuator Faults Research Articles

Adjustable Order Fault Estimation Observer Based Fault‐Tolerant Control for Nonlinear Switched Stochastic Systems With Partially Unknown Nonlinear Dynamics

ABSTRACTThe fault estimation and fault‐tolerant control problems of switching stochastic systems with partially unknown nonlinear dynamics, external disturbance, actuator, and sensor faults are studied. A new observer and disturbance observer are constructed to simultaneously estimate the system state, actuator, and sensor faults, as well as modelable disturbances. The dimensions of the proposed adjustable dimension observer are not fixed and can be adjusted within a certain range, and unknown nonlinear dynamics can be decoupled. According to estimated information, fault‐tolerant controller is designed. The sufficient condition is obtained to ensure that the root‐mean‐square gain from the disturbances to the fault reconstruction error is bounded. Finally, two simulation examples are provided to verify the effectiveness of the proposed method.

Anti-disturbance reliable memory feedback tracking control for unmanned aerial vehicle systems

The problem of memory feedback tracking control for unmanned aerial vehicle systems subject to nonlinear actuator faults and disturbances is investigated in this paper. First, a generalized extended state observer is constructed to get the estimates of the system states and the disturbances. Then, by incorporating the obtained estimates in the control design, an anti-disturbance memory feedback tracking control law is designed such that the resulting closed-loop augmented system is asymptotically stable, and thereby the states of the unmanned aerial vehicle system track the given reference trajectories with satisfactory disturbance rejection performance. Notably, by constructing appropriate asymmetric Lyapunov–Krasovskii functional, the stability and stabilization conditions for guaranteeing the desired tracking and disturbance attenuation performance are derived in terms of linear matrix inequalities. Further, the observer gains are evaluated using the pole placement approach. Finally, numerical simulations are given to verify that the proposed control strategy is viable.

Robust Fuzzy Adaptive Fault‐Tolerant Control for a Class of Second‐Order Nonlinear Systems

ABSTRACTIn this brief, an optimal active fuzzy fault‐tolerant control (OAFFTC) scheme is proposed for a class of unknown perturbed multi‐input multi‐output (MIMO) nonlinear systems with nonaffine nonlinear actuator faults and time‐varying sensor faults. The control strategy can handle automatically (online updating) with three additives (bias, drift, and loss of accuracy) along with one multiplicative (loss of effectiveness) sensor faults and nonlinear state‐dependent actuator faults. In order to deal with uncertain system dynamics, sensor and actuator faults, and external disturbances, fuzzy systems (FSs) and backstepping techniques were combined to provide the adaptive control term as well as a robust control term. Butterworth filter is used to get rid the algebraic loop problem. The suggested robust term, can deal with approximation errors of the fuzzy systems (FSs). To automatically optimize the adaptive parameters and the starting conditions, particle swarm optimization (PSO) approach is introduced. The Lyapunov approach is employed to demonstrate the closed‐loop system's stability. To assess the efficacy and correctness of the suggested scheme, quadrotor dynamic model is performed on the simulation part.

Modeling and vibration suppression for overhead crane in planar space with nonlinear time-varying actuator faults and uncertain control directions

Modeling and vibration suppression for overhead crane in planar space with nonlinear time-varying actuator faults and uncertain control directions

Modeling and vibration suppression based on Nussbaum function for beam bridge with unknown control directions and unknown nonlinear time-varying actuator faults

In this paper, the modeling of the beam bridge system with in-domain control and the vibration suppression under unknown control directions, unknown nonlinear time-varying actuator faults and external disturbances are studied. The beam bridge with fixed ends can be regarded as Euler Bernoulli beam, which is a typical distributed parameter system. Firstly, the partial differential equation (PDE) model of the beam bridge is established according to Hamilton principle. Then, an adaptive in-domain control scheme based on Nussbaum function is designed on the PDE model to eliminate the vibration of the beam bridge. It is proved theoretically that all closed-loop signals are uniformly bounded under this control law, and the vibration of the system asymptotically converges to zero. The simulation results also prove the effectiveness of the proposed control scheme. What’ more, the modeling and control scheme presented in this paper can be applied to a class of systems similar to beam bridges, such as vibration suppression of the main beam of an overhead crane bridge.

Practical prescribed-time fuzzy tracking control for uncertain nonlinear systems with time-varying actuators faults

The paper investigates the practical prescribed-time fuzzy tracking control problem for a category of nonlinear system subject to time-varying actuator faults. The presence of unknown nonlinear dynamics and actuator faults makes achieving tracking control within a prescribed-time challenging. To tackle this issue, we propose a novel practical prescribed-time fuzzy tracking control strategy, which is independent of the initial state of the system and does not rely on precise modeling of the system and actuators. We apply the approximation capabilities of fuzzy logic systems to handle the unknown nonlinear functions and unidentified actuator faults in the system. The piecewise controller and adaptive law constructed based on piecewise prescribed time-varying function and backstepping technique method establish the theoretical framework of practical prescribed-time tracking control, and extend the range of prescribed-time tracking control to infinity. Regardless of the initial conditions, the proposed control strategy can guarantee that all signals remain uniformly bounded within the practical prescribed time in the presence of unknown nonlinear item and time-varying actuator faults. Simulation example is presented to demonstrate the effectiveness of the proposed control strategy.

Optimal adaptive fuzzy fault-tolerant control applied on a quadrotor attitude stabilization based on particle swarm optimization

This article discusses the problem of stabilizing the attitude control of a quadrotor system, which is subject to uncertainty, external disturbances, and sensor and actuator faults. To address these challenges, the control stage employs universal approximators, such as fuzzy systems, which estimate the system’s uncertainties and eliminate nonaffine nonlinear actuator faults. In addition, the particle swarm optimization technique is used to adjust the adaptive parameters and fuzzy initial values. The robust control term is carefully designed to handle approximation errors, time-varying sensors, and external disturbances. To solve the issue of the unavoidable algebraic loop during the actuator approximation phase, a Butterworth low-pass filter is integrated. This approach automatically deals with external disturbances, and no further approximation is necessary. Furthermore, the controller can be reconfigured online to enable fast-fault compensation without requiring a fault detection or isolation unit. To prove the global stability and boundedness of all signals in the closed-loop system, Lyapunov theory is used.

Adaptive fuzzy fault‐tolerant control for cooperative output regulation with unknown nonlinear disturbances and actuator faults

AbstractThe cooperative output regulation problem with actuator faults and unknown nonlinear disturbances is a challenging research area in multi‐agent systems. This paper proposes an adaptive fuzzy fault‐tolerant controller to address this problem by employing a fuzzy logic system for approximating the unknown nonlinear disturbances. The internal model principle is utilized to transform the cooperative output regulation problem into a stability problem of an auxiliary system, with the aim of compensating for actuator failures in the system. By incorporating fuzzy logic system, the adaptive controller is able to approximate and compensate for the unknown nonlinear disturbances. Extensive simulations are conducted to validate the robustness and performance of the proposed method. The adaptive controller effectively handles actuator faults and achieves output regulation with unknown nonlinear disturbances.

Input–output finite-time stabilisation for periodic piecewise polynomial systems with nonlinear actuator faults: an observer-based approach

This paper is concerned with the input–output finite-time (IO-FT) stabilisation problem for a class of continuous-time periodic piecewise polynomial systems (PPPSs) with immeasurable states and external disturbances via state estimation-based robust reliable controller. Firstly, to reflect the actuality, a parameter uncertainty that exhibits the random nature and the actuator faults with nonlinear character are considered in the addressed PPPSs and the control scheme, respectively. In detail, the randomness of uncertain parameters is portrayed by the stochastic variable and it is presumed to pursue the Bernoulli distributions. Secondly, to estimate the immeasurable states of PPPSs, a periodic piecewise polynomial observer is designed depending on the output of PPPSs. The main intent of this article is to devise a state estimation-based robust reliable controller to ascertain the IO-FT stabilisation of the PPPSs. Moreover, by bridging the Lyapunov stability theory, linear matrix inequality technique and IO-FT stability theory, the required IO-FT stabilisation conditions in the frame of linear matrix inequality are procured for the system under consideration. Eventually, simulation results of the addressed PPPSs are shown in line with the proposed analytical findings, revealing the competence, inherent capability and utility of the devised control protocol.

Discrete-time robust event-triggered actuator fault-tolerant control based on adaptive networks and reinforcement learning

This paper focuses on the topic of fault-tolerant control for discrete-time systems with nonlinear uncertainties and actuator faults. It considers both passive and active faults as part of the analysis and design. The proposed adaptive controller, based on a nonlinear electronic circuit, handles offset-biasing, sensitivity variation, and dead-zone effects. An event-triggered mechanism, utilizing a sliding surface, enhances robustness and reduces data transmission. Adaptive networks called MiFRENs are employed, trained using reinforcement learning. Theoretical analysis guarantees boundedness of internal signals and tracking error. Experimental results validate the scheme, demonstrating required conditions, reduced data transmission, and robust performance. Comparative evaluations confirm its superiority

Observer-Based Finite-Time Fault-Tolerant Control for Nonstrict-Feedback Nonlinear Systems With Multiple Uncertainties

In the fault-tolerant control (FTC) tasks of nonstrict-feedback nonlinear systems, unmeasurable states, disturbance, and actuator faults are recognized as the main factors that obstacle the effective controller design and, thus, the tracking performance improvement. To tackle these obstructions, a fuzzy observer is introduced to address the difficulties of the unmeasurable states involving nonstrict-feedback nonlinear systems by benefiting from the approximation property of fuzzy logic systems. Owing to the newly employed damping term in the intermediate control law being utilized to compensate for the possibly unlimited number of faults, the proposed FTC strategy is able to deal with actuator faults properly without imposing tighter requirements on the fault mechanism. To reach fast transient performance, stability of finite time is reached by exploiting the backstepping method. The investigated strategy ensures that all the responses of the systems are semiglobal practical finite-time stable. Meanwhile, the tracking error converges to a small neighborhood of the origin within finite time. In addition, to demonstrate its effectiveness, the provided approach is applied to the position tracking of a robotic system, which shows anticipated control performances in spite of various uncertainties.

Adaptive control for a class of flexible mechanical systems with bending deformation and torsion deformation in the presence of nonlinear time-varying actuator faults and unknown control directions

Vibration control problem of a class of flexible mechanical systems with bending deformation and torsion deformation in the presence of nonlinear time-varying actuator faults and unknown control directions is considered in this paper. The dynamics model of this kind of flexible mechanical system, which includes two kinds of coupled vibration deformation and unknown nonlinear disturbances, is composed of some partial differential equations. In order to overcome the control difficulty brought by unknown control directions and time-varying nonlinear actuator faults, a Nussbaum function based adaptive boundary controller is designed to suppress the bending and twist vibration deformations of the mechanical system. The stability of the system is proved by Lyapunov direct method, and the effectiveness of the proposed control scheme is verified by numerical simulation at the end of this paper.

Decentralized adaptive PI fault tolerant tracking control for strong interconnected nonlinear systems subject to unmodeled dynamics and actuator faults

In this study, a novel decentralized adaptive proportional–integral (PI) fault tolerant tracking control strategy is proposed for a class of strong interconnection nonlinear systems with unmodeled dynamics and actuator faults. The adverse effects generated by unmodeled dynamics could be eliminated by introducing a dynamic signal and the multiplicative actuator faults could be dealt with by using adaptive control technique. In addition, broad learning system (BLS) scheme is used to approximate the unknown nonlinear functions and additive actuator faults, the minimal-learning-parameter (MLP) scheme is used in this study to reduce the number of adaptive update parameters, which resltus in less computation overhead. The decentralized adaptive PI fault tolerant tracking controller including a switching compensation mechanism is designed for the considered interconnected systems, such that all the signals in the closed-loop systems are uniformly ultimately bounded (UUB) and the tracking errors converge to a small residual set. In the end, a chemical reactor example is utilized to illustrate the feasibility and significance of the designed control scheme.

General fuzzy adaptive fault-tolerant control based on Nussbaum-type function with additive and multiplicative sensor and state-dependent actuator faults

The present paper devotes to propose a general active fault-tolerant control (GAFTC) for a class of unknown multi-input multi-output (MIMO) nonlinear systems that are subject to simultaneous additive and multiplicative sensor and nonaffine nonlinear state-dependent actuator faults, exogenous disturbances and multiple unknown control directions. By combining fuzzy logic systems and back-stepping technique, an adaptive control unit along with a robust control unit are developed. In the proposed approach, the unknown dynamics along with sensor and non-affine nonlinear state-dependent actuator faults are approximated to avoid developing fault detection and isolation unit. Furthermore, the difficulty caused by the unknown control gain directions is solved by using the Nussbaum-type function. The adaptation mechanism is proposed to overcome fuzzy approximation errors and exogenous disturbances, and the Butterworth low-pass filter is adopted to get rid of the algebraic loop appearing in the actuator faults approximation. The stability of the closed-loop system is proved by Lyapunov method where all the signals involved in the resulting closed-loop system are shown to be bounded, and the tracking errors converge asymptotically to the origin. Quadrotor attitude dynamics stabilization is proposed in the simulation study to test the accuracy and the effectiveness of the proposed control scheme.

Fuzzy-Based Robust Precision Consensus Tracking for Uncertain Networked Systems With Cooperative–Antagonistic Interactions

In bipartite consensus tracking (BCT) tasks for nonlinear multiagent systems, stochastic disturbances and actuator faults are regarded as essential factors that hamper effective controller formulation and tracking precision improvement. To address these difficulties, we design an improved finite-time performance function (FTPF) for a fuzzy fault-tolerant distributed cooperative control scheme to achieve finite-time robust precision BCT tasks for nonlinear multiagent systems. The parameter selection range of the improved FTPF is relaxed, which renders systems to achieve better transient performance. Benefitting from stochastic Lyapunov stability theory, it is shown that all signals of systems are semi-global uniformly ultimately bounded in probability, and bipartite consensus errors can satisfy the arbitrary precision with probability in the predefined time. Finally, to verify its effectiveness, the proposed control scheme is applied to BCT tasks of a group of vehicles, which manifests anticipated control performance under various uncertainties.

Fuzzy Fault-Tolerant Control Applied on Two Inverted Pendulums with Nonaffine Nonlinear Actuator Failures

This paper deals with the problem of fault-tolerant control for a class of perturbed nonlinear systems with nonlinear non-affine actuator faults. Fuzzy systems are integrated into the design of the control law to get rid of the system nonlinearities and the considered actuator faults. Two adaptive controllers are proposed in order to reach the control objective and ensure stability. The first term is an adaptive controller involved to mollify the system uncertainties and the considered actuator faults. Therefore, the second term is known as a robust controller introduced for the purpose of dealing with approximation errors and exogenous disturbances. In general, the designed controller allows to deal automatically with the exogenous disturbances and actuator faults with the help of an online adaption protocol. A Butterworth low-pass filter is utilized to avoid the algebraic loop issue and allows a reliable approximation of the ideal control law. A stability study is performed based on Lyapunov's theory. Two inverted pendulum example is carried out to prove the accuracy of the controller.

Fault-Tolerant Attitude Control Incorporating Reconfiguration Control Allocation for Supersonic Tailless Aircraft

This paper presents a fault-tolerant attitude control scheme, incorporating reconfiguration control allocation for supersonic tailless aircraft subject to nonlinear characteristics, actuator constraint, uncertainty, and actuator faults. The main idea is to propose an incremental reconfiguration closed-loop control allocation scheme, coupled with a basic backstepping attitude controller, to achieve attitude control. Based on the virtual control input generated by the basic backstepping attitude controller, firstly, the incremental nonlinear control allocation method is adopted to deal with the nonlinear characteristics and actuator constraint. Secondly, a distribution error feedback loop is constructed in the incremental nonlinear control allocation method to enhance the robustness against the uncertainty of the control effectiveness matrix. Thirdly, the control effectiveness matrix is reconstructed by different kinds of fault information to deal with actuator faults, and the proper combination of actuator deflections is generated to achieve accurate command tracking. The stability of the proposed scheme is guaranteed by the Jury stability criterion and the Lyapunov stability analysis. Finally, in comparison with the three existing approaches, the simulation results of two cases are provided to show the effectiveness of the proposed scheme.

Distributed output estimation error observer‐based adaptive fault‐tolerant consensus tracking control of multi‐agent systems

SummaryThe purpose of this study is to discuss the fully distributed design of output estimation error observer and fault‐tolerant consensus tracking control for a class of multi‐agent systems with Lipschitz nonlinear dynamics and actuator faults. Firstly, based on the relative output measurements of neighboring agents, the distributed output estimation error observer is developed to adaptively estimate the state and fault information of each agent, and further overcome the difficulties of online updating the adaptive estimations of unknown hyper‐parameters. Secondly, to achieve the state consensus tracking goal and compensate for the negative effects of actuator faults, the distributed fault‐tolerant consensus tracking control scheme is proposed on the basis of the state estimation and adaptive fault estimation information, and has excellent robustness and consensus tracking control performance. Moreover, sufficient criteria can ensure that consensus tracking error of each agent converges to a small set near the origin. Finally, numerical simulations are provided to show the effectiveness of the proposed fully distributed algorithm.

Anti-disturbance observer-based control for fuzzy chaotic semi-Markov jump systems with multiple disturbances and mixed actuator failures

This article develops robust stabilization and anti-disturbance control design for fuzzy chaotic semi-Markov jump systems with randomly occurring uncertainties, nonlinear actuator faults, matched and mismatched disturbances. Primarily, the matched disturbances stimulated from the exogenous systems are dealt with by constructing a disturbance observer. At the same time, mismatched part is handled by the extended passivity performance. Additionally, the actuator fault model which encompasses both linear and nonlinear characteristics is put forward in the controller design. Thus, by taking advantage of the parallel distributed compensation methodology, a composite anti-disturbance control is framed by combining the fuzzy rule-based nonlinear fault-tolerant controller and estimation of the disturbance. Thereafter, by selecting relevant mode-dependent Lyapunov function candidate, adequate criteria are acquired in the context of linear matrix inequalities to ensure robust asymptotic stability along with the endorsed extended passivity performance level for the closed-loop system. In due course, by solving the developed inequalities under the aegis of MATLAB platform, the gain matrices of the devised controller and the framed disturbance observer are obtained. Last of all, to validate the effectiveness and applicability of the theoretical findings, simulation results of standard Chua’s circuit system, Lorenz system and Rössler system are exploited.

Finite-Time Adaptive Cooperative Fault-Tolerant Control for Multi-Agent System With Hybrid Actuator Faults

Aiming at the uncertain parameters and transient instability of the system caused by the actuator fault of the multiagent system, this article adopts the radial basis function neural networks to approximate unknown nonlinear function. Then, a novel adaptive fault-tolerant controller is designed based on the combination back-stepping technology and dynamic surface technology to compensate the unknown nonlinear hybrid actuator faults, thereby improving the fault tolerance of the system. Furthermore, the designed controller can guarantee the transient stability of the system through finite-time theory and Lyapunov stability theory. Finally, the comparison of two simulation examples is given to verify the effectiveness of the designed controller, which provided an effective research idea for engineering practice.